Log in
Enquire now
‌

US Patent 11531873 Convolution acceleration with embedded vector decompression

OverviewStructured DataIssuesContributors

Contents

TimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
115318731
Patent Inventor Names
Carmine Cappetta1
Giuseppe Desoli1
Surinder Pal Singh1
Thomas Boesch1
Date of Patent
December 20, 2022
1
Patent Application Number
169096731
Date Filed
June 23, 2020
1
Patent Citations
‌
US Patent 10394929 Adaptive execution engine for convolution computing systems
‌
US Patent 10417364 Tool to create a reconfigurable interconnect framework
1
‌
US Patent 10417560 Neural network unit that performs efficient 3-dimensional convolutions
1
‌
US Patent 10438115 Neural network unit with memory layout to perform efficient 3-dimensional convolutions
‌
US Patent 10452605 Method and apparatus for task scheduling on heterogeneous multi-core reconfigurable computing platform
‌
US Patent 10482155 Winograd algorithm on a matrix processing architecture
‌
US Patent 10546211 Convolutional neural network on programmable two dimensional image processor
‌
US Patent 10552222 Task scheduling method and apparatus on heterogeneous multi-core reconfigurable computing platform
...
Patent Citations Received
‌
US Patent 12118451 Deep convolutional network heterogeneous architecture
10
‌
US Patent 11836608 Convolution acceleration with embedded vector decompression
11
‌
US Patent 11880759 Vector quantization decoding hardware unit for real-time dynamic decompression for parameters of neural networks
12
‌
US Patent 12073308 Hardware accelerator engine
13
‌
US Patent 12079158 Reconfigurable neural engine with extensible instruction set architecture
14
Patent Primary Examiner
‌
Peguy Jean Pierre
1
CPC Code
‌
G06N 3/063
1
‌
H03M 7/3082
1
‌
H03M 7/6005
1

Techniques and systems are provided for implementing a convolutional neural network. One or more convolution accelerators are provided that each include a feature line buffer memory, a kernel buffer memory, and a plurality of multiply-accumulate (MAC) circuits arranged to multiply and accumulate data. In a first operational mode the convolutional accelerator stores feature data in the feature line buffer memory and stores kernel data in the kernel data buffer memory. In a second mode of operation, the convolutional accelerator stores kernel decompression tables in the feature line buffer memory.

Timeline

No Timeline data yet.

Further Resources

Title
Author
Link
Type
Date
No Further Resources data yet.

References

Find more entities like US Patent 11531873 Convolution acceleration with embedded vector decompression

Use the Golden Query Tool to find similar entities by any field in the Knowledge Graph, including industry, location, and more.
Open Query Tool
Access by API
Golden Query Tool
Golden logo

Company

  • Home
  • Press & Media
  • Blog
  • Careers
  • WE'RE HIRING

Products

  • Knowledge Graph
  • Query Tool
  • Data Requests
  • Knowledge Storage
  • API
  • Pricing
  • Enterprise
  • ChatGPT Plugin

Legal

  • Terms of Service
  • Enterprise Terms of Service
  • Privacy Policy

Help

  • Help center
  • API Documentation
  • Contact Us
By using this site, you agree to our Terms of Service.